Wait, did anyone else think option A was talking about shrinking the model like a laundry mishap? 'Helps decrease the model's complexity' - what is this, model dry cleaning?
Option B is clearly the correct answer. Ongoing pre-training helps the model continuously learn and improve its performance over time. This is the whole point of fine-tuning a foundation model.
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